ПРОЯВЛЕНИЯ СЕРДЕЧНОЙ НЕДОСТАТОЧНОСТИ У МУЖЧИН МОЛОЖЕ 60 ЛЕТ С ИНФАРКТОМ МИОКАРДА, ОСЛОЖНЕННЫМ ОСТРЫМ ПОВРЕЖДЕНИЕМ ПОЧЕК

Abstract

Relevance. Acute kidney injury in myocardial infarction worsens its prognosis, including due to the development of chronic heart failure. Moreover, most of the data was obtained for patients over 60 years old. Aim. To evaluate the features of the heart failure manifestations in men under 60 years old with myocardial infarction complicated by acute kidney injury to improve prevention and outcomes. Material and methods. The study included men 19-60 years old with type I myocardial infarction. The patients were divided into two age-comparable groups: I - study group, with acute kidney injury - 25 patients; II - control, without it - 486 patients. A comparative analysis of the heart failure main manifestations frequency in the first 48 hours (1) and at the end of the third week of the disease (2), their dynamics, analysis of their impact on the risk of chronic heart failure development in acute kidney injury (ANOVA) was performed. Results. The study group (4.0%) differed from the control (21.8%) in a lower frequency of acrocyanosis (p = 0.03) and liver enlargement (8.0 and 25.7%; respectively; p = 0.046) at the end of the eighth week diseases. The main risk markers of the chronic heart failure development in study group were: winter period of the year (absolute risk: 94.1%; relative - 3.76; p = 0.0003), respiratory infections 2-3 times a year (absolute risk: 81.8%; p = 0.003), left ventricular myocardial mass index1 ≥ 173.3 g/m2 (absolute risk: 100%; p = 0.008) and mean arterial pressure1 ≥ 120 mm Hg (absolute risk: 100%; relative - 1.88; p = 0.01). Conclusions. Men under 60 years old with acute kidney injury in myocardial infarction are characterized by a higher incidence of chronic heart failure. The listed above values of the different predictors should be used in the formation of the high-risk groups for the chronic heart failure in acute kidney injury development, as well as for prognostic modeling.